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These are the Julia codes for the electical impedance tomography (EIT) experiments of the manuscripts:

\n\n

It is based on the codes for the previous article

\n\n

However, due to several optimisation performed, running the code for those experiments will no longer produce the same results.

\n

Prerequisites

\n

These codes were written for Julia 1.12. The Julia package prequisites are from March 2026 when our experiments were run. You may get Julia from julialang.org.

\n

Using

\n

Navigate your unix shell to the directory containing this README.md and then run:

\n
$ julia --project=.\n
\n

The first time doing this, to ensure all the dependencies are installed, run

\n
$ ]instantiate\n
\n

Afterwards in the Julia shell, type:

\n
> using PredictPDPSEIT\n
\n

This may take a while as Julia precompiles the code. Then, to generate all the experiments in Dynamic inverse problems: single-loop online algorithms, run:

\n
> RunAllExperiments()\n> PlotAllExperiments()\n
\n

To generate the data for the asymptotic regularisation illustration in Dynamic inverse problems: online regularisation theory, run:

\n
> PredictPDPSEIT.simulate_regularisation_experiments()\n> PredictPDPSEIT.run_regularisation_experiments()\n> PredictPDPSEIT.plot_regularisation_experiments()
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